How to use data to set prices (without a data team)

You don't need a data team to use data for pricing. You need three columns, a habit, and a guardrail. Here's the smallest useful version of the practice — then a path to scale it.

The minimum viable dataset

Three fields per SKU is enough to start:

• Cost — what you pay (landed, not list)
• Current price — what you charge today
• At least one competitor URL — the price you are most often compared against

That's it. If you have sales velocity, stock, and traffic — even better. But none of those are blockers.

Step 1: find the under-priced items

Sort your catalogue by (competitor_median_price - your_price) / your_price. The SKUs at the top are priced below market — investigate why. Sometimes it's MAP. Sometimes it's a deliberate loss leader. Often it's nothing — just inertia. Those are pure margin sitting on the table.

Step 2: protect the floor

Before changing any price, decide your minimum acceptable margin. Set a hard floor — the price cannot go below it, ever, for any reason. This single rule prevents the most common failure mode of data-driven pricing: chasing a competitor into a margin hole.

Step 3: raise where the data says you can

For items where you're already at or above market median and sales velocity is healthy, raise 3–8%. Measure conversion for 2 weeks. If it holds, raise another notch. If it drops, revert. This is the entire loop. It works.

Step 4: drop only when the data demands

Don't drop prices because a competitor did. Drop them when your data shows conversion responding. The competitor being cheaper doesn't matter if customers are still buying from you.

Step 5: write down the rule

The biggest difference between data-driven and gut-feel pricing isn't the data — it's that the rule is written down. "If competitor median > my price by 5% AND velocity > X, raise by Y" is a rule you can audit, improve, and hand to a tool. "Whatever feels right" is not.

When to graduate to a tool

When you have more than ~50 SKUs and the manual loop costs more than a few hours a week, an engine becomes the right investment. Luska checks competitor prices daily, flags undercuts, and on the Professional plan recommends prices inside a built-in minimum margin and a cap on each change — see the full playbook.